predictFactoryHealth

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It states the predictive nature and time range, which implies a safe read-only operation, but it does not explicitly disclose that no data is modified, nor does it describe the return format or underlying data requirements. Some behavioral context is present but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no redundant words. Every word contributes to the core purpose, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema, annotations, and parameters, the description must carry all context. It clearly conveys the tool's function and temporal scope but leaves some ambiguity about the exact output structure and what 'operational indicators' encompass. Still, it is sufficiently complete for a simple prediction tool with no invocation parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema is empty with zero parameters, so the schema trivially covers all properties. The description adds no parameter information, but none is needed for a parameterless tool, aligning with the baseline of 4 for zero-parameter tools.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('predicts') and a clear resource ('overall factory health score trends'), distinguishing it from sibling tools like predictMachineFailure and getFactoryKPIs. It clearly states the expected output domain and time horizon.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The purpose implicitly suggests use when future factory health trends are needed, but it does not provide explicit guidance on when to prefer this tool over alternatives like analyzeFactory or getFactoryKPIs. No exclusions or alternative comparisons are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.